from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 14.0 | 3.525326 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 7.207122 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 12.574277 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 39.063415 |
| KMeans_tall | 0.0 | 1.0 | 37.948737 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 11.784298 |
| KMeans_short | 0.0 | 0.0 | 17.437895 |
| daal4py_KMeans_short | 0.0 | 0.0 | 7.610057 |
| LogisticRegression | 0.0 | 0.0 | 58.422084 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 52.107584 |
| Ridge | 0.0 | 0.0 | 0.966038 |
| daal4py_Ridge | 0.0 | 0.0 | 0.649127 |
| total | 0.0 | 30.0 | 9.369231 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.137 | 0.002 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.480 | 0.003 | 0.285 | 0.000 | See |
| 1 | KNeighborsClassifier | predict | 0.162 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 0.086 | 0.002 | 1.889 | 0.007 | See |
| 2 | KNeighborsClassifier | predict | 25.170 | 0.701 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 1.843 | 0.074 | 13.659 | 0.002 | See |
| 3 | KNeighborsClassifier | fit | 0.130 | 0.004 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.479 | 0.009 | 0.271 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.168 | 0.016 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.083 | 0.001 | 2.035 | 0.009 | See |
| 5 | KNeighborsClassifier | predict | 33.982 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 1.807 | 0.053 | 18.809 | 0.001 | See |
| 6 | KNeighborsClassifier | fit | 0.129 | 0.004 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.475 | 0.007 | 0.272 | 0.001 | See |
| 7 | KNeighborsClassifier | predict | 0.168 | 0.015 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.083 | 0.002 | 2.041 | 0.009 | See |
| 8 | KNeighborsClassifier | predict | 34.145 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 1.850 | 0.047 | 18.457 | 0.001 | See |
| 9 | KNeighborsClassifier | fit | 0.127 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.484 | 0.010 | 0.262 | 0.001 | See |
| 10 | KNeighborsClassifier | predict | 0.175 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 0.080 | 0.000 | 2.176 | 0.000 | See |
| 11 | KNeighborsClassifier | predict | 12.510 | 0.122 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 1.854 | 0.044 | 6.748 | 0.001 | See |
| 12 | KNeighborsClassifier | fit | 0.134 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.467 | 0.003 | 0.287 | 0.001 | See |
| 13 | KNeighborsClassifier | predict | 0.185 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.082 | 0.003 | 2.269 | 0.001 | See |
| 14 | KNeighborsClassifier | predict | 23.377 | 0.387 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 1.798 | 0.038 | 13.003 | 0.001 | See |
| 15 | KNeighborsClassifier | fit | 0.129 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.481 | 0.008 | 0.269 | 0.001 | See |
| 16 | KNeighborsClassifier | predict | 0.186 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.081 | 0.001 | 2.300 | 0.000 | See |
| 17 | KNeighborsClassifier | predict | 23.162 | 0.110 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 1.845 | 0.052 | 12.552 | 0.001 | See |
| 18 | KNeighborsClassifier | fit | 0.050 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.094 | 0.006 | 0.535 | 0.005 | See |
| 19 | KNeighborsClassifier | predict | 0.018 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.005 | 0.001 | 3.359 | 0.089 | See |
| 20 | KNeighborsClassifier | predict | 20.803 | 0.016 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.274 | 0.017 | 76.054 | 0.004 | See |
| 21 | KNeighborsClassifier | fit | 0.049 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.104 | 0.003 | 0.474 | 0.002 | See |
| 22 | KNeighborsClassifier | predict | 0.032 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.006 | 0.001 | 5.339 | 0.051 | See |
| 23 | KNeighborsClassifier | predict | 28.892 | 0.076 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.266 | 0.005 | 108.698 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.054 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.094 | 0.003 | 0.575 | 0.002 | See |
| 25 | KNeighborsClassifier | predict | 0.033 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.005 | 0.001 | 6.174 | 0.021 | See |
| 26 | KNeighborsClassifier | predict | 29.099 | 0.015 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.316 | 0.006 | 92.119 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.053 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.096 | 0.003 | 0.556 | 0.001 | See |
| 28 | KNeighborsClassifier | predict | 0.013 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.006 | 0.001 | 2.257 | 0.017 | See |
| 29 | KNeighborsClassifier | predict | 10.025 | 0.093 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.284 | 0.009 | 35.360 | 0.001 | See |
| 30 | KNeighborsClassifier | fit | 0.054 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.100 | 0.003 | 0.542 | 0.002 | See |
| 31 | KNeighborsClassifier | predict | 0.028 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.006 | 0.001 | 4.537 | 0.014 | See |
| 32 | KNeighborsClassifier | predict | 18.928 | 0.212 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.289 | 0.007 | 65.517 | 0.001 | See |
| 33 | KNeighborsClassifier | fit | 0.065 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.094 | 0.003 | 0.694 | 0.003 | See |
| 34 | KNeighborsClassifier | predict | 0.028 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 4.587 | 0.012 | See |
| 35 | KNeighborsClassifier | predict | 18.632 | 0.397 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.345 | 0.011 | 54.040 | 0.001 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.794 | 0.091 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.691 | 0.023 | 4.045 | 0.002 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 8.917 | 0.169 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.434 | 0.009 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.094 | 0.002 | 4.596 | 0.001 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.730 | 0.069 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.689 | 0.011 | 3.962 | 0.001 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 9.699 | 0.329 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.842 | 0.015 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.179 | 0.002 | 4.707 | 0.000 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.021 | 0.067 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.685 | 0.029 | 4.409 | 0.002 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 3.977 | 0.153 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.699 | 0.051 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.537 | 0.015 | 5.026 | 0.001 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.710 | 0.116 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.699 | 0.022 | 3.874 | 0.003 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 3.491 | 0.325 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.700 | 0.019 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.096 | 0.003 | 7.259 | 0.002 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.749 | 0.130 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.700 | 0.014 | 3.930 | 0.003 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.300 | 0.301 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.292 | 0.051 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.181 | 0.004 | 7.125 | 0.002 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.733 | 0.097 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.747 | 0.025 | 3.657 | 0.002 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 2.061 | 0.246 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.392 | 0.152 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.562 | 0.012 | 7.812 | 0.002 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.228 | 0.037 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.490 | 0.010 | 2.506 | 0.001 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 18.935 | 0.477 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.027 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 24.024 | 0.141 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.201 | 0.037 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.507 | 0.012 | 2.369 | 0.002 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 18.402 | 0.498 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.028 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 21.763 | 0.149 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.198 | 0.058 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.504 | 0.019 | 2.376 | 0.004 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 19.251 | 0.531 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.043 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.009 | 0.002 | 5.031 | 0.046 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.140 | 0.037 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.481 | 0.013 | 2.367 | 0.002 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.157 | 0.457 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 26.555 | 0.085 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.179 | 0.041 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.474 | 0.014 | 2.485 | 0.002 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.612 | 0.524 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 19.607 | 0.137 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.169 | 0.028 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.479 | 0.013 | 2.441 | 0.001 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 5.217 | 0.496 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.051 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 7.135 | 0.036 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.605 | 0.015 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.431 | 0.026 | 1.403 | 0.004 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.015 | 0.511 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.956 | 0.403 | See |
| 3 | KMeans_tall | fit | 0.523 | 0.018 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.397 | 0.016 | 1.315 | 0.003 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.398 | 0.503 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.191 | 0.504 | See |
| 6 | KMeans_tall | fit | 6.119 | 0.098 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.873 | 0.042 | 2.130 | 0.000 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.142 | 0.510 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.183 | 0.527 | See |
| 9 | KMeans_tall | fit | 5.684 | 0.109 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.688 | 0.043 | 2.114 | 0.001 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.316 | 0.421 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.345 | 0.242 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.298 | 0.019 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 22.0 | NaN | 0.095 | 0.005 | 3.134 | 0.007 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.919 | 0.439 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.219 | 0.138 | See |
| 3 | KMeans_short | fit | 0.110 | 0.004 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.041 | 0.002 | 2.665 | 0.003 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.040 | 0.512 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.145 | 0.183 | See |
| 6 | KMeans_short | fit | 0.759 | 0.028 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 19.0 | NaN | 19.0 | NaN | 0.326 | 0.021 | 2.328 | 0.006 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.971 | 0.427 | See |
| 8 | KMeans_short | predict | 0.005 | 0.001 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 3.667 | 0.165 | See |
| 9 | KMeans_short | fit | 0.230 | 0.022 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 27.0 | NaN | 30.0 | NaN | 0.170 | 0.014 | 1.357 | 0.016 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.946 | 0.351 | See |
| 11 | KMeans_short | predict | 0.003 | 0.001 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 2.405 | 0.285 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 10.624 | 0.043 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 10.929 | 0.253 | 0.972 | 0.001 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.373 | 0.733 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.959 | 0.256 | See |
| 3 | LogisticRegression | fit | 0.693 | 0.022 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 0.742 | 0.040 | 0.935 | 0.004 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.001 | 0.093 | 1.461 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.004 | 0.000 | 0.430 | 0.041 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.038 | 0.001 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.021 | 0.001 | 1.820 | 0.003 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.637 | 1.191 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.677 | 0.376 | See |
| 3 | Ridge | fit | 0.008 | 0.000 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.005 | 0.003 | 1.532 | 0.283 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.652 | 1.239 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.681 | 0.356 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
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"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
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{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
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"user_api": "openmp",
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}